Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/152467
Title: Chaos for optimization
Authors: Guo, Yao
Keywords: Engineering::Computer science and engineering::Theory of computation::Analysis of algorithms and problem complexity
Issue Date: 2021
Publisher: Nanyang Technological University
Source: Guo, Y. (2021). Chaos for optimization. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/152467
Abstract: Optimization is the process to find the optimal solution from possible solutions. However, in many practical optimization problems, the number of feasible solutions has exploded with the size of the problem, which makes it impossible to obtain the global optimal solution. Chaos is a kind of random-like movement generated from a nonlinear system. Many researchers demonstrate that a series of nonlinear characteristics of chaos, ergodicity, non-periodic, randomness, etc., can improve the randomness and speed when searching optimal solutions within a short time. This dissertation presents a state-of-the-art review of chaos for optimization. The related works are reviewed from chaotic approaches and optimization applications. Then simulation experiments of several chaos optimization algorithms are given in detail. Finally, the superiority of chaos and two factors affecting performance are discussed, as well as some future research directions are provided.
URI: https://hdl.handle.net/10356/152467
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

Files in This Item:
File Description SizeFormat 
Chaos for Optimization_Revised.pdf
  Restricted Access
1.87 MBAdobe PDFView/Open

Page view(s)

191
Updated on Dec 9, 2022

Download(s)

1
Updated on Aug 19, 2021

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.